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benchmarkactiveprovisionaltonebank-51219110·1 events·first seen 42h ago

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5arXiv · cs.CL·42h ago·source ↗

ORBIT: Training-free multi-attribute behavioral steering via orthogonal subspace rotation

Researchers introduce ORBIT (Orthogonal Rotation-Based Intervention Technique), a training-free activation steering method that simultaneously controls multiple behavioral attributes in language models. The approach constructs a joint subspace from per-attribute steering planes via SVD and applies a single norm-preserving rotation, avoiding the norm imbalance and directional cancellation problems of naive vector summation. The authors also release TraitFactory, a new multi-attribute behavioral benchmark, and evaluate across Llama-3.2-3B, Qwen-2.5-7B, and Llama-3.1-8B. ORBIT outperforms existing training-free baselines on multi-attribute steering while better preserving output coherence.